Summary of work: A correlation method was developed to examine functional interactions between brain regions, by correlating regional cerebral blood flows (rCBF) as determined by positron emission tomography (PET) in humans. Correlations of blood flow with exogenous variables also could be examined. During a reading task, the angular gyrus was found to be functionally connected to visual processing and language areas in normals, and functionally disconnected from these regions in dyslexics. During a face matching task in which task difficulty was systematically changed (by adding noise to the images), brain functional interactions changed from involving regions doing predominantly perceptual processing to involving greater interactions between frontal lobe regions. In a study of response time during a motor preparation task, cerebellar rCBF was negatively correlated with response time. A systems-level neural network model, fitted to rCBF PET data, permitted determination of the brain regions and their interactions that were involved in a working memory for faces task. A large-scale neural model was developed to relate PET data to the temporal and spatial activity of neuronal populations during specific cognitive tasks. Using this model, simulations of a delayed-match-to-sample task for features were performed. Using nonlinear kernel analysis, the transformation of PET images of Alzheimer's disease patients into stereotactic space was found to produce errors that correlated with dementia severity.